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The admittance of a manipulator can be used to improve robotic assembly. If properly selected, the admittance will regulate a contact force and use it to guide the parts to proper positioning. In previous work, procedures for selecting the appropriate admittance for single principal contact (PC) cases were identified. This paper extends this research for some of the two PC cases--those for which each contact occurs at a single point. The conditions obtained ensure that the motion that results from frictionless contact always instantaneously reduces part misalignment. We show that, for bounded misalignments, if an admittance satisfies the misalignmentreducing conditions at a finite number of contact configurations, then the admittance will also satisfy the conditions at all intermediate configurations. Index Terms--Assembly, compliance selection, multiple-point contact, spatial admittance.

By judiciously selecting the admittance of a manipulator, the forces of contact that occur during assembly can be used to guide the parts to proper positioning. This paper identifies conditions for selecting the appropriate spatial admittance to achieve reliable force-guided assembly of polyhedral parts for cases in which a single feature (vertex, edge, or face) of one part contacts a single feature of the other, i.e., all single principal contact cases. These conditions ensure that the motion that results from frictionless contact always instantaneously reduces part misalignment. We show that, for bounded misalignments, if an admittance satisfies the misalignment-reducing conditions at a finite number of contact configurations, then the admittance will also satisfy the conditions at all intermediate configurations. Index Terms--Assembly, compliance selection, spatial admittance.

An important issue in the development of force guidance assembly strategies is the specification of an appropriate admittance control law. This paper identifies conditions to be satisfied when selecting the appropriate admittance to achieve force-guided assembly of polygonal parts for multipoint contact with friction. These conditions restrict the admittance behavior for each of the various one-point and two-point contact cases and ensure that the motion that results from contact reduces part misalignment for each case. We show that, for bounded friction and part misalignments, if the identified conditions are satisfied for a finite number of contact configurations and friction coefficients, the conditions ensure that force guidance is achieved for all configurations and values of friction within the specified bounds. Index Terms--Admittance, assembly, compliance selection, frictional contact.

Admittance control approaches show significant promise in providing reliable force-guided assembly. An important issue in the development of these approaches is the specification of an appropriate admittance control law. This paper identifies procedures for selecting the appropriate admittance to achieve reliable force-guided assembly of planar polyhedral parts for single-point contact cases. A set of conditions that are imposed on the admittance matrix is presented. These conditions ensure that the motion that results from contact reduces part misalignment. We show that, for bounded misalignments, if an admittance satisfies the misalignment-reduction conditions at a finite number of contact configurations, then the admittance will also satisfy the conditions at all intermediate configurations. Index Terms--Admittance, assembly, compliance selection.

In this paper, we identify the space of spatial compliant behavior that can be achieved through the use of simple springs connected in parallel to a single rigid body. Here, the expression "simple spring" refers to the set of compliant relations associated with passive translational springs and rotational springs. The restriction on the stiffness matrices (the same restriction previously identified using Lie Algebra for a parallel network of active or passive translational springs) is derived using screw theory by investigating the compliant behavior of individual simple springs. We show that the restriction results from the fact that simple springs can only provide either a pure force or a pure torque to the suspended body (not a combination). We show that the 20-dimensional subspace of "realizable" spatial stiffness matrices achieved with parallel simple springs is defined by a linear necessary and sufficient condition on the positive semidefinite stiffness matrix. A procedure to synthesize an arbitrary full-rank stiffness matrix within this realizable subspace is provided. This procedure requires no more than seven simple springs. Index Terms - Impedance design, multidimensional impedance, spatial compliant mechanisms.

Abstract Background Numerous studies have used microarrays to identify gene signatures for predicting cancer patient clinical outcome and responses to chemotherapy. However, the potential impact of gene expression profiling in cancer diagnosis, prognosis and development of personalized treatment may not be fully exploited due to the lack of consensus gene signatures and poor understanding of the underlying molecular mechanisms. Methods We developed a novel approach to derive gene signatures for breast cancer prognosis in the context of known biological pathways. Using unsupervised methods, cancer patients were separated into distinct groups based on gene expression patterns in one of the following pathways: apoptosis, cell cycle, angiogenesis, metastasis, p53, DNA repair, and several receptor-mediated signaling pathways including chemokines, EGF, FGF, HIF, MAP kinase, JAK and NF-κB. The survival probabilities were then compared between the patient groups to determine if differential gene expression in a specific pathway is correlated with differential survival. Results Our results revealed expression of cell cycle genes is strongly predictive of breast cancer outcomes. We further confirmed this observation by building a cell cycle gene signature model using supervised methods. Validated in multiple independent datasets, the cell cycle gene signature is a more accurate predictor for breast cancer clinical outcome than the previously identified Amsterdam 70-gene signature that has been developed into a FDA approved clinical test MammaPrint®. Conclusion Taken together, the gene expression signature model we developed from well defined pathways is not only a consistently powerful prognosticator but also mechanistically linked to cancer biology. Our approach provides an alternative to the current methodology of identifying gene expression markers for cancer prognosis and drug responses using the whole genome gene expression data.

Abstract Background NCI60 cell lines are derived from cancers of 9 tissue origins and have been invaluable in vitro models for cancer research and anti-cancer drug screen. Although extensive studies have been carried out to assess the molecular features of NCI60 cell lines related to cancer and their sensitivities to more than 100,000 chemical compounds, it remains unclear if and how well these cell lines represent or model their tumor tissues of origin. Identification and confirmation of correct origins of NCI60 cell lines are critical to their usage as model systems and to translate in vitro studies into clinical potentials. Here we report a direct comparison between NCI60 cell lines and primary tumors by analyzing global gene expression profiles. Results Comparative analysis suggested that 51 of 59 cell lines we analyzed represent their presumed tumors of origin. Taking advantage of available clinical information of primary tumor samples used to generate gene expression profiling data, we further classified those cell lines with the correct origins into different subtypes of cancer or different stages in cancer development. For example, 6 of 7 non-small cell lung cancer cell lines were classified as lung adenocarcinomas and all of them were classified into late stages in tumor progression. Conclusion Taken together, we developed and applied a novel approach for systematic comparative analysis and integrative classification of NCI60 cell lines and primary tumors. Our results could provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screenings. Moreover, this gene expression profile based approach can be generally applied to evaluate experimental model systems such as cell lines and animal models for human diseases.

In this paper, the structure of spatial stiffness is investigated by evaluating the stiffness matrix "primitives"--the rank-1 matrices that compose a spatial stiffness matrix. Although the decomposition of a rank-2 or higher stiffness matrix into the sum of rank-1 matrices is not unique, one property of the set of matrices is conserved. This property, defined as the stiffness-coupling index, identifies how the translational and rotational components of the stiffness are related. Here, we investigate the stiffness-coupling index of the rank-1 matrices that compose a spatial stiffness matrix. We develop a matrix decomposition that yields a set of rank-1 stiffness matrices that identifies the bounds on the stiffness-coupling index for any decomposition. This decomposition, referred to as the eigenscrew decomposition, is shown to be invariant in coordinate transformation. With this decomposition, we provide some physical insight into the behavior associated with a general spatial stiffness matrix. Index Terms--Multidimensional impedance, spatial compliant behavior, spatial stiffness and compliance.

In this paper, we address the spatial elastic behavior that can be achieved through the use of a serial chain of revolute and prismatic elastic joints. We show that, regardless of the number of joints or the configuration of the links, there exists a subspace within the 21-dimensional compliance matrix space that cannot be reached by a simple serial elastic mechanism. This restriction is shown to be dual to the restriction on the stiffness matrices associated with simple parallel mechanisms. Although analogous to each other, the two restrictions correspond to different elastic behaviors, A procedure to synthesize any realizable compliance matrix with a simple serial mechanism is provided. The dualities and differences between the parallel and serial cases are discussed. Index Terms--Compliance realization, serial mechanism, spatial compliance.

Affymetrix''s high-density oligonucleotide arrays offer an exciting technology in biomedical research. With more and more statistical involvement in every step of the process, there has been a constant effort to make sure that the expression data are appropriately extracted in the first place. According to Affymetrix GeneChip technology, each gene is represented by 11–20 oligo probe pairs; the challenge is how to extract one meaningful number, expression, from the 11–20 pairs of numbers. More specifically, there is first a need to differentiate the components of specific binding, nonspecific binding, and optical background noise in both PM and MM probes, and then an expression measure that is proportional to the true abundance of transcripts is to be derived. A new method, SUM, which sums up PM and MM values and then follows a process similar to that of RMA, is considered. The performance of SUM is investigated and compared to the three most popular methods, MAS5, dChip, and RMA. The assessments are based on a well-controlled experiment dataset that is publicly available. The results show that in several respects the performance of SUM is comparable to that of RMA and dChip, and all three of these methods show some advantages over MAS5. There is some evidence showing that SUM has higher differential sensitivity than other methods in certain situations. [Copyright &y& Elsevier]

Using the simulated data set from Genetic Analysis Workshop 13, we explored the advantages of using longitudinal data in genetic analyses. The weighted average of the longitudinal data for each of seven quantitative phenotypes were computed and analyzed. Genome screen results were then compared for these longitudinal phenotypes and the results obtained using two cross-sectional designs: data collected near a single age (45 years) and data collected at a single time point. Significant linkage was obtained for nine regions (LOD scores ranging from 5.5 to 34.6) for six of the phenotypes. Using cross-sectional data, LOD scores were slightly lower for the same chromosomal regions, with two regions becoming nonsignificant and one additional region being identified. The magnitude of the LOD score was highly correlated with the heritability of each phenotype as well as the proportion of phenotypic variance due to that locus. There were no false-positive linkage results using the longitudinal data and three false-positive findings using the cross-sectional data. The three false positive results appear to be due to the kurtosis in the trait distribution, even after removing extreme outliers. Our analyses demonstrated that the use of simple longitudinal phenotypes was a powerful means to detect genes of major to moderate effect on trait variability. In only one instance was the power and heritability of the trait increased by using data from one examination. Power to detect linkage can be improved by identifying the most heritable phenotype, ensuring normality of the trait distribution and maximizing the information utilized through novel longitudinal designs for genetic analysis.